Evidence map›Paper›PMID 34849412›Full record

ArticleClinical and translational radiation oncology2022

Online adaptive radiotherapy for head and neck cancers on the MR linear Accelerator: Introducing a novel modified Adapt-to-Shape approach.

Amit Gupta, Alex Dunlop, Adam Mitchell, Dualta McQuaid, Simeon Nill, Helen Barnes, Kate Newbold, Chris Nutting, Shreerang Bhide, Uwe Oelfke and 2 more

Abstract read
In one paragraph

Article in Clinical and translational radiation oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed.

  1. Article
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  9. Risk analysis of the Unity 1.5T MR-Linac adapt-to-shape workflow.Journal of applied clinical medical physics · 2025
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  16. Adaptive assessment based on fractional CBCT images for cervical cancer.Journal of applied clinical medical physics · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Amit GuptaThe Royal Marsden NHS Foundation Trust and the Institute of Cancer Research, Head & Neck Unit, 15 Cotswold Road, Sutton, London SM2 5NG, United Kingdom.
Alex DunlopThe Joint Department of Physics, The Royal Marsden Hospital and the Institute of Cancer Research; Downs Road, Sutton SM2 5PT, United Kingdom.
Adam MitchellThe Joint Department of Physics, The Royal Marsden Hospital and the Institute of Cancer Research; Downs Road, Sutton SM2 5PT, United Kingdom.
Dualta McQuaidThe Joint Department of Physics, The Royal Marsden Hospital and the Institute of Cancer Research; Downs Road, Sutton SM2 5PT, United Kingdom.
Simeon NillThe Joint Department of Physics, The Royal Marsden Hospital and the Institute of Cancer Research; Downs Road, Sutton SM2 5PT, United Kingdom.
Helen BarnesThe Royal Marsden NHS Foundation Trust; Downs Road, Sutton SM2 5PT, United Kingdom.
Kate NewboldThe Royal Marsden NHS Foundation Trust; Downs Road, Sutton SM2 5PT, United Kingdom.
Chris NuttingThe Royal Marsden NHS Foundation Trust and the Institute of Cancer Research, Head & Neck Unit, 15 Cotswold Road, Sutton, London SM2 5NG, United Kingdom.
Shreerang BhideThe Royal Marsden NHS Foundation Trust and the Institute of Cancer Research, Head & Neck Unit, 15 Cotswold Road, Sutton, London SM2 5NG, United Kingdom.
Uwe OelfkeThe Joint Department of Physics, The Royal Marsden Hospital and the Institute of Cancer Research; Downs Road, Sutton SM2 5PT, United Kingdom.
Kevin Joseph HarringtonThe Royal Marsden NHS Foundation Trust and the Institute of Cancer Research, Head & Neck Unit, 15 Cotswold Road, Sutton, London SM2 5NG, United Kingdom.
Kee Howe WongThe Royal Marsden NHS Foundation Trust; Downs Road, Sutton SM2 5PT, United Kingdom.

Funding

Cancer Research UK 19727Cancer Research UK 21993Medical Research Council MC_EX_MR/M009068/1Medical Research Council MR/M009068/1
6 · The paper itself

Abstract

introductionThe Elekta Unity MR-Linac (MRL) has enabled adaptive radiotherapy (ART) for patients with head and neck cancers (HNC). Adapt-To-Shape-Lite (ATS-Lite) is a novel Adapt-to-Shape strategy that provides ART without requiring daily clinician presence to perform online target and organ at risk (OAR) delineation. In this study we compared the performance of our clinically-delivered ATS-Lite strategy against three Adapt-To-Position (ATP) variants: Adapt Segments (ATP-AS), Optimise Weights (ATP-OW), and Optimise Shapes (ATP-OS).

methodsTwo patients with HNC received radical-dose radiotherapy on the MRL. For each fraction, an ATS-Lite plan was generated online and delivered and additional plans were generated offline for each ATP variant. To assess the clinical acceptability of a plan for every fraction, twenty clinical goals for targets and OARs were assessed for all four plans.

results53 fractions were analysed. ATS-Lite passed 99.9% of mandatory dose constraints. ATP-AS and ATP-OW each failed 7.6% of mandatory dose constraints. The Planning Target Volumes for 54 Gy (D95% and D98%) were the most frequently failing dose constraint targets for ATP. ATS-Lite median fraction times for Patient 1 and 2 were 40 mins 9 s (range 28 mins 16 s - 47 mins 20 s) and 32 mins 14 s (range 25 mins 33 s - 44 mins 27 s), respectively.

conclusionsOur early data show that the novel ATS-Lite strategy produced plans that fulfilled 99.9% of clinical dose constraints in a time frame that is tolerable for patients and comparable to ATP workflows. Therefore, ATS-Lite, which bridges the gap between ATP and full ATS, will be further utilised and developed within our institute and it is a workflow that should be considered for treating patients with HNC on the MRL.

Indexed as

Adaptive RadiotherapyHead and Neck NeoplasmsMR-guided RadiotherapyMR-Linac

Identifiers

PMID34849412
PMCPMC8608651

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.